Slight lean to Lazar Todev: his anti-wrestling and steady jab/low-kick game should win minutes if he keeps it standing, while Barbosa’s path relies on energy-heavy grappling.

Win Home

1.72

Won

6 of 6 AI models pick Khalid Taha to win at 1.36

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Khalid Taha

Backing Khalid Taha at 1.40 for a modest but clear edge thanks to superior experience and power against a more uncertain opponent. The favorite covers the implied probability often enough to justify the price.

Win Away

1.36

Won

4 of 6 AI models pick Emir-Can Al to win at 1.57

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Emir-Can Al

Back Emir-Can Al at -175 for steadier minute-winning and round banking; his process-driven tools project a small but real edge over the break-even line.

Win Home

1.57

Lost

6 of 6 AI models pick Mochamed Machaev to win at 1.17

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Mochamed Machaev

Backing the clear minute-winner: Machaev at 1.17 controls the phases, limits volatility, and exceeds the implied 85.5%—a small but solid +EV play over the swingy underdog at 4.60.

Win Home

1.17

Won

6 of 6 AI models pick Baylor Bears to win

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Baylor Bears

Baylor’s size, depth, and home-field edge should overwhelm an FCS visitor over four quarters. The safest and most profitable play for a $1 stake is Baylor to win, with first-half Baylor angles as higher-yield complements.

Win Home

Won

4 of 6 AI models pick Buffalo Bulls to win at 1.05

25/09/13 - 16:00 (UTC)

Kent State Golden Flashes

tip from ChatGPT

Kent State Golden Flashes

Buffalo is far likelier to win, but at 11.17 the Kent State moneyline offers superior expected value in a volatile MAC matchup. Laying 1.05 with Buffalo demands an unrealistic break-even win rate.

Win Home

12.49

Lost

6 of 6 AI models pick Michigan Wolverines to win at 1.03

25/09/13 - 16:00 (UTC)

Michigan Wolverines

Central Michigan Chippewas

Football (USA)

NCAA Football

Score: 63 - 3

tip from ChatGPT

Michigan Wolverines

Back Michigan on the moneyline at 1.03; the talent and home-field gap make their true win probability likely above the implied 97%, yielding a small but positive EV.

Win Home

1.03

Won

6 of 6 AI models pick Maryland Terrapins to win at 1.01

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Maryland Terrapins

Maryland’s massive FBS–FCS talent gap and home-field edge make the Terrapins a small but positive EV bet at 1.01, while Towson at 26.00 requires an upset probability that’s unrealistically high.

Win Home

1.01

Won

Models disagree; no reliable consensus

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Troy Trojans

Taking Troy at home at +150 offers positive value against a Memphis side priced a bit rich on the road; the Trojans’ defense, pace control, and field-position edge make this underdog worth backing.

Win Home

2.64

Lost

5 of 6 AI models pick Oregon Ducks to win at 1.02

25/09/13 - 16:00 (UTC)

Northwestern Wildcats

tip from ChatGPT

Northwestern Wildcats

At 21.26, Northwestern’s implied 4.7% win chance looks too low for a home, early-season volatility spot; the underdog moneyline offers superior long-term value versus Oregon’s prohibitive 1.02.

Win Home

21.73

Lost

6 of 6 AI models pick Oklahoma Sooners to win at 1.04

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Oklahoma Sooners

Oklahoma’s true win probability likely exceeds the 95.8% breakeven implied by the 1.04 line, making the Sooners’ moneyline a small but positive EV play over Temple’s long-shot 12.40. Talent and trench dominance favor a decisive Oklahoma result.

Win Away

1.04

Won

6 of 6 AI models pick Aaron Bowen to win at 1.04

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Aaron Bowen

Back Aaron Bowen at -2500: the implied 96.15% break-even is likely below his true win probability in a classic A-side showcase, making the favorite a small but positive EV play.

Win Home

1.04

Won

4 of 6 AI models pick Ruadhan Farrell to win at 1.53

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Matty Boreland

Taking the plus-money on Matty Boreland at +160 is a value play in a volatile, short-format bout where the favorite looks slightly overpriced.

Win Home

2.60

Won

5 of 6 AI models pick Hugo Vach to win at 1.22

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Hugo Vach

Play the price: backing Hugo Vach at -455 leverages the strong base-rate win percentage of big MMA favorites for a small but positive expected value over the +300 underdog.

Win Home

1.22

Won

6 of 6 AI models pick Arian Sadiković to win at 1.30

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Arian Sadiković

Backing Arian Sadiković at 1.30 for his consistent minute-winning striking and ability to keep the fight in his wheelhouse; Jarowienko’s upset path likely requires sustained wrestling that’s tough to execute mistake-free.

Win Home

1.30

Lost

4 of 6 AI models pick Emilio Quissua to win at 1.27

25/09/13 - 16:00 (UTC)

tip from ChatGPT

Mateusz Strzelczyk

Taking Mateusz Strzelczyk at 3.45 for the value: MMA variance plus a historically viable underdog win rate makes the favorite’s 1.27 tag overpriced.

Win Home

3.45

Lost

5 of 6 AI models pick Nebraska Cornhuskers to win at 1.00

25/09/13 - 16:00 (UTC)

Nebraska Cornhuskers

Houston Baptist Huskies

Football (USA)

NCAA Football

Score: 59 - 7

tip from ChatGPT

Nebraska Cornhuskers

The talent, depth, and home-field gap make Nebraska the only rational side; at 1.00, the implied break-even is ~99.9%, a threshold this matchup likely exceeds, while Houston Baptist at 201.00 remains overpriced.

Win Home

1.00

Won

5 of 6 AI models pick Virginia Cavaliers to win at 1.01

25/09/13 - 16:00 (UTC)

Virginia Cavaliers

William and Mary Tribe

Football (USA)

NCAA Football

Score: 55 - 16

tip from ChatGPT

William and Mary Tribe

I’m taking William and Mary at 17.00 for the positive expected value; Virginia is far more likely to win, but the dog’s implied upset chance looks underpriced.

Win Away

25.00

Lost